Protocol for microbial profiling of low biomass upper respiratory tract samples

Mari-Lee Odendaal, Mei Ling J N Chu, Kayleigh Arp, Gina J van Beveren, Giske Biesbroek, Justyna Binkowska, Thijs Bosch, James A. Groot, Raiza Hasrat, Sjoerd Kuiling, Elske M. Van Logchem, Paula Lusarreta Parga, Wouter de Steenhuijsen Piters, Debby Bogaert

Research output: Contribution to journalArticlepeer-review

Abstract

The microbiome of the human upper respiratory tract (URT) has a considerably lower bacterial biomass compared, for example, to the well-studied gut microbiome. In particular, the nasal cavity and nasopharynx exhibit a low bacterial biomass of around 103 bacteria per swab2,3. Consequently, environmental contamination can become a major issue when analyzing low-biomass samples, obscuring the true microbiota signal4,5. Besides, the ratio of host to bacterial DNA is also significantly higher, leading to increased contamination from host genomic DNA6. To address these challenges, it is crucial to perform studies in controlled laboratory environments with standardized procedures.

This protocol was developed to investigate the microbial community composition of the human URT, focusing on saliva, oropharynx and nasopharynx samples7-9. Unlike protocols designed for high-biomass samples, such as feces, which often use robots, this is not feasible for low-density samples, as too much material would be lost. Laboratory procedures have been first meticulously benchmarked to accommodate low-biomass samples10. Additionally, this protocol has been successfully applied to other sample types, including bronchoalveolar lavage (BAL), tracheal aspirates, nasal lavages, sputum, early life (low biomass) feces, breastmilk, vagina and skin7,11-15. The protocol presented here outlines detailed procedures to extract DNA from URT samples, quantify total bacterial biomass using quantitative Polymerase Chain Reaction (qPCR), and reliably construct 16S rRNA gene libraries. The protocol also provides guidance on performing downstream bioinformatics analysis.
Original languageEnglish
Article number103740
Pages (from-to)103740
JournalSTAR Protocols
Volume6
Issue number2
Early online date8 Apr 2025
DOIs
Publication statusE-pub ahead of print - 8 Apr 2025

Keywords / Materials (for Non-textual outputs)

  • Bioinformatics
  • Health Sciences
  • Microbiology
  • Molecular Biology
  • Sequence analysis
  • Sequencing

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